Acoustic Emission Techniques for the Nondestructive Evaluation of TBCs Under Thermal Cycling Conditions
Bibliographic record
Abstract
Abstract A thermal cycling test was designed in order to predict thermal barrier coatings (TBC) life of combustion chambers. The thermal cycle is produced by two 2kW halogen lamps highly focused on the TBC. A 25X100 mm TBC is plasma sprayed centered onto a substrate 25X300 mm. The thermal cycling can be done either under argon atmosphere or air in order to be able to discriminate the oxidation induced acoustic emissions from the expansion mismatch. Two transducers located at each end of the substrate monitor the acoustic signals emitted by crack initiation and/or propagation. The advantage of using two transducers is that with a time of flight approach cracking phenomena can be located along the TBC. This process allows the study of welded substrates coated with TBC, TBC coated around holes and to check for the presence of cracks by using metallography preparation. The challenge of the test is to use the early cycles emission signatures in order to predict the long term durability of the TBC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".